Project description:BACKGROUND:Data on the clinical features, optimal treatment and outcomes of paediatric patients with epithelioid sarcoma (ES) are limited and mostly retrospective. METHODS:A subset analysis of ES patients < 30 years of age enrolled on two international prospective clinical trials conducted between 7/2005 and 11/2015 was performed. Risk-adapted therapy was based on tumour diameter, histologic grade, extent of surgery and presence/absence of metastases and included surgery ± radiotherapy for all patients with the addition of ifosfamide/doxorubicin chemotherapy for intermediate-/high-risk patients. Response to therapy, event-free and overall survival and pattern and predictors of treatment failure were evaluated. RESULTS:Sixty-three ES patients (median age 13.1 years, 52% male) were eligible. Clinical features included the following: 68% extremity, median tumour diameter 3.5 cm, 56% high histologic grade, 14% nodal metastases, 14% distant metastases. Thirty-four low-risk patients underwent surgery (n = 30) or surgery/radiotherapy (n = 4); 16 intermediate-risk and 13 high-risk patients received chemotherapy ± surgery ± radiotherapy. Partial response was observed in 11/22 (50%) patients receiving neoadjuvant therapy. Events were local recurrence (n = 10) and distant recurrence (n = 15); estimated 5-year survival was 86.4%, 63.5% and 0%, respectively, for low-, intermediate- and high-risk patients. Locoregional nodal involvement, invasive tumour, high grade and lesser extent of resection predicted event-free survival in patients without metastases. CONCLUSIONS:Most low-risk ES patients who have undergone an adequate resection fare well without adjuvant therapy. Large tumour size, high histologic grade, tumour invasiveness, inadequate tumour resection and metastatic disease predict poorer outcomes in higher risk ES patients, for whom more effective therapies are needed. CLINICAL TRIAL REGISTRATION:COG ARST0332: ClinicalTrials.gov Identifier NCT00346164, EpSSG NRSTS 2005: European Union Drug Regulating Authorities Clinical Trials No. 2005-001139-31.

Project description:PurposeThe aim of this paper is to better define the clinical features and outcomes of young patients with non-rhabdomyosarcoma soft tissue sarcoma (NRSTS) with regional and distant lymph node (LN) metastases treated in a standardised fashion, we analysed LN involvement in COG study ARST0332, which evaluated a risk-based treatment strategy for young patients with all stages of NRSTS.Patients and methodsPatients <30 years old with newly diagnosed NRSTS and LN metastases enrolled on ARST0332 were studied. Regional LN sampling was required for those with epithelioid sarcoma, clear cell sarcoma or clinically/radiographically enlarged LNs. Tumour features and extent of pre-enrolment resection determined treatment, including chemotherapy, radiotherapy, and delayed surgery. Recommendations for LN metastases included LN dissection at the time of primary tumour resection and dose-adapted radiotherapy based on extent of LN resection.ResultsTwenty of 529 eligible and evaluable ARST0332 patients with NRSTS had LN metastases; epithelioid sarcoma had the highest incidence (18%, 5 of 28). Pre-treatment imaging identified LN enlargement in 19 of 20 patients; 1 had no pre-treatment LN imaging. At 6.9 years median follow-up for surviving patients, 5-year overall survival was 85.7% (95% CI: 33.4%, 97.9%) for seven patients with isolated LN metastases and 15.4% (95% CI: 2.5%, 38.8%) for 13 patients with additional extranodal metastases. LN recurrence occurred in only one patient without LNs sampled at initial diagnosis.ConclusionLN metastases occur in about 4% of paediatric/young adult NRSTS, are limited to a few histologic subtypes, and are rare in patients who did not have clinical or imaging evidence of lymphadenopathy, suggesting that biopsies of non-enlarged LNs are not necessary to identify occult involvement. Patients with isolated LN metastases have high 5-year overall survival (∼85%) and should be treated with curative intent.ClinicaltrialsGov registry noNCT00346164.

Project description:PAPER 1:"Identification of novel subgroups of high-risk pediatric precursor B acute lymphoblastic leukemia (B-ALL) by unsupervised microarray analysis: clinical correlates and therapeutic implications. A Children's Oncology Group (COG) study." ABSTRACT We examined gene expression profiles of pre-treatment specimens from 207 patients from the COG P9906 study to identify signatures of children with high risk B-precursor acute lymphoblastic leukemia (ALL) and to determine whether the resulting clusters are associated with either specific clinical features or treatment response characteristics. Four unsupervised clustering methods were utilized to classify patients into similar groups. The different clustering algorithms showed significant overlap in cluster membership. Two clusters contained all cases with either t(1;19)(q23;p13) translocations or MLL rearrangements. The other six clusters were novel and had no recurring chromosomal abnormalities or distinctive clinical features. Members of two of these novel clusters had significant survival differences when compared to the overall 4-year relapse-free survival (RFS) of 61%. These included clusters of patients with either significantly better (94.7%) or worse (21.0%) RFS at 4 years. Children of Hispanic/Latino ethnicity were disproportionately present in the poor outcome cluster. The poor outcome cluster represents a novel biologically distinctive subset of B-precursor ALL that may occur at least as frequently as BCR/ABL. Further molecular characterization of this cluster may lead to the discovery of genomic abnormalities that can be targeted to improve the currently dismal outcome for children with this gene signature. The Sample data have also been used in another study: PAPER 2: "Gene expression classifiers for minimal residual disease and relapse free survival improve outcome prediction and risk classification in children with high risk acute lymphoblastic leukemia. A Children's Oncology Group study". ABSTRACT Background. Nearly 25% of children with B-precursor ALL present with "high-risk" disease (HR-ALL) that is resistant to current therapies. Gene expression profiling may yield molecular classifiers for outcome prediction that can be used to improve risk classification and therapeutic targeting. Methods. Expression profiles were obtained in pre-treatment leukemic samples from 207 uniformly treated children with HR-ALL. Relapse free survival (RFS) was 61% at 4 years and flow cytometric measures of minimal residual disease (MRD) at the end of induction (day 29) were predictive of outcome (P<0.001). Molecular classifiers predictive of RFS and MRD were developed using extensive cross-validation procedures. Results. A 38 gene molecular risk classifier predictive of RFS (MRC-RFS) distinguished two groups in HR-ALL with different relapse risks: low (4 yr RFS: 81%, n=109) vs. high (4 yr RFS: 50%, n=98) (P<0.0001). In multivariate analysis, the best predictor combined MRC-RFS and day 29 flow MRD data, classifying children into low (87% RFS), intermediate (62% RFS), or high risk (29% RFS) groups (P<0.0001). A 21 gene molecular classifier predictive of MRD could effectively substitute for day 29 flow MRD, yielding a combined classifier that similarly distinguished three risk groups at pre-treatment (low: 82% RFS; intermediate: 63% RFS; and high risk: 45% RFS) (P<0.0001). This combined molecular classifier was further validated on an independent cohort of 84 children with HR-ALL (P = 0.006). Conclusions. Molecular classifiers predictive of RFS and MRD can be used to distinguish distinct prognostic groups within HR-ALL, significantly improving risk classification schemes and the ability to prospectively identify children at diagnosis who will respond to or fail current treatment regimens. NOTE: Due to Children's Oncology Group (COG) restrictions, outcome and MRD data cannot be provided as part of the covariate data for this dataset at the present time. If you would like to arrange individual access to this data, please contact COG or the PI of this study, Dr. Cheryl Willman, at the University of New Mexico Cancer Center (cwillman@unm.edu) to arrange a collaboration.

Project description:PAPER 1:"Identification of novel subgroups of high-risk pediatric precursor B acute lymphoblastic leukemia (B-ALL) by unsupervised microarray analysis: clinical correlates and therapeutic implications. A Children's Oncology Group (COG) study." ABSTRACT We examined gene expression profiles of pre-treatment specimens from 207 patients from the COG P9906 study to identify signatures of children with high risk B-precursor acute lymphoblastic leukemia (ALL) and to determine whether the resulting clusters are associated with either specific clinical features or treatment response characteristics. Four unsupervised clustering methods were utilized to classify patients into similar groups. The different clustering algorithms showed significant overlap in cluster membership. Two clusters contained all cases with either t(1;19)(q23;p13) translocations or MLL rearrangements. The other six clusters were novel and had no recurring chromosomal abnormalities or distinctive clinical features. Members of two of these novel clusters had significant survival differences when compared to the overall 4-year relapse-free survival (RFS) of 61%. These included clusters of patients with either significantly better (94.7%) or worse (21.0%) RFS at 4 years. Children of Hispanic/Latino ethnicity were disproportionately present in the poor outcome cluster. The poor outcome cluster represents a novel biologically distinctive subset of B-precursor ALL that may occur at least as frequently as BCR/ABL. Further molecular characterization of this cluster may lead to the discovery of genomic abnormalities that can be targeted to improve the currently dismal outcome for children with this gene signature. The Sample data have also been used in another study: PAPER 2: "Gene expression classifiers for minimal residual disease and relapse free survival improve outcome prediction and risk classification in children with high risk acute lymphoblastic leukemia. A Children's Oncology Group study". ABSTRACT Background. Nearly 25% of children with B-precursor ALL present with "high-risk" disease (HR-ALL) that is resistant to current therapies. Gene expression profiling may yield molecular classifiers for outcome prediction that can be used to improve risk classification and therapeutic targeting. Methods. Expression profiles were obtained in pre-treatment leukemic samples from 207 uniformly treated children with HR-ALL. Relapse free survival (RFS) was 61% at 4 years and flow cytometric measures of minimal residual disease (MRD) at the end of induction (day 29) were predictive of outcome (P<0.001). Molecular classifiers predictive of RFS and MRD were developed using extensive cross-validation procedures. Results. A 38 gene molecular risk classifier predictive of RFS (MRC-RFS) distinguished two groups in HR-ALL with different relapse risks: low (4 yr RFS: 81%, n=109) vs. high (4 yr RFS: 50%, n=98) (P<0.0001). In multivariate analysis, the best predictor combined MRC-RFS and day 29 flow MRD data, classifying children into low (87% RFS), intermediate (62% RFS), or high risk (29% RFS) groups (P<0.0001). A 21 gene molecular classifier predictive of MRD could effectively substitute for day 29 flow MRD, yielding a combined classifier that similarly distinguished three risk groups at pre-treatment (low: 82% RFS; intermediate: 63% RFS; and high risk: 45% RFS) (P<0.0001). This combined molecular classifier was further validated on an independent cohort of 84 children with HR-ALL (P = 0.006). Conclusions. Molecular classifiers predictive of RFS and MRD can be used to distinguish distinct prognostic groups within HR-ALL, significantly improving risk classification schemes and the ability to prospectively identify children at diagnosis who will respond to or fail current treatment regimens. NOTE: Due to Children's Oncology Group (COG) restrictions, outcome and MRD data cannot be provided as part of the covariate data for this dataset at the present time. If you would like to arrange individual access to this data, please contact COG or the PI of this study, Dr. Cheryl Willman, at the University of New Mexico Cancer Center (cwillman@unm.edu) to arrange a collaboration. Unsupervised clustering and supervised risk classification analyses of 207 diagnostic samples and associated clinical covariate data. See the Summary for greater details. The data were analyzed using Microarray Suite version 5.0 (MAS 5.0) in the Affymetrix Gene Chip Operating Software Version 1.4. Probe masking was used (see 9906_TT207_Affymetrix_probe_mask.msk, linked below as a supplementary file). Otherwise all Affymetrix default parameter settings were used. Global scaling as the normalization method, with the default target intensity of 500, was used.

Dataset Information

Surgery alone is sufficient therapy for children and adolescents with low-risk synovial sarcoma: A joint analysis from the European paediatric soft tissue sarcoma Study Group and the Children's Oncology Group.

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Surgery alone is sufficient therapy for children and adolescents with low-risk synovial sarcoma: A joint analysis from the European paediatric soft tissue sarcoma Study Group and the Children's Oncology Group.

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